REPOGEO REPORT · LITE
PRIME-RL/SimpleVLA-RL
Default branch main · commit 7c51662d · scanned 6/23/2026, 6:23:11 AM
GitHub: 1,737 stars · 113 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface PRIME-RL/SimpleVLA-RL, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highabout#1Expand 'VLA' in the repository description to clarify its domain
Why:
CURRENT[ICLR 2026] SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
COPY-PASTE FIX[ICLR 2026] SimpleVLA-RL: Scaling Vision-Language-Action (VLA) Model Training for Robotics via Reinforcement Learning
- highreadme#2Reposition the README's opening paragraph to explicitly state the project's domain
Why:
CURRENT## SimpleVLA-RL: Open RL Framework for Vision–Language–Action Models **SimpleVLA-RL** is an efficient RL framework for VLA that improves long-horizon planning under data scarcity. It leverages reinforcement learning that can substantially outperforms SFT in simulation and real-world tasks, reveals a "pushcut" new-action phenomenon, and strengthens spatial/object/goal generalization.
COPY-PASTE FIX## SimpleVLA-RL: Open RL Framework for Vision–Language–Action (VLA) Models in Robotics **SimpleVLA-RL** is an efficient open-source reinforcement learning (RL) framework specifically designed for training and scaling Vision-Language-Action (VLA) models for robot manipulation. It addresses challenges in long-horizon planning and data scarcity, outperforming SFT in simulation and real-world tasks, and strengthening spatial, object, and goal generalization.
- mediumtopics#3Add more specific topics related to robotics and VLA models
Why:
CURRENTreasoning, rl, vla
COPY-PASTE FIXreasoning, rl, vla, robotics, robot-manipulation, vision-language-models, long-horizon-planning
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Ray · recommended 1×
- RLlib · recommended 1×
- Kubernetes · recommended 1×
- Kubeflow · recommended 1×
- Argo Workflows · recommended 1×
- CATEGORY QUERYHow to scale vision-language-action model training efficiently for long-horizon planning with RL?you: not recommendedAI recommended (in order):
- Ray
- RLlib
- Kubernetes
- Kubeflow
- Argo Workflows
- PyTorch Lightning
- OpenSpiel
- Google Cloud Vertex AI
- AWS SageMaker
- Azure Machine Learning
- Dask
AI recommended 11 alternatives but never named PRIME-RL/SimpleVLA-RL. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking an open framework for real-world reinforcement learning on complex dexterous manipulation tasks.you: not recommendedAI recommended (in order):
- RLBench (https://github.com/deepmind/rlbench)
- RoboStack (https://github.com/RoboStack/robostack)
- ROS (Robot Operating System) (https://github.com/ros)
- Conda (https://github.com/conda/conda)
- NVIDIA Isaac Gym (https://github.com/NVIDIA-Omniverse/IsaacGymEnvs)
- MuJoCo (https://github.com/deepmind/mujoco)
- Stable Baselines3 (https://github.com/DLR-RM/stable-baselines3)
- RLLib (https://github.com/ray-project/ray)
- Franka Emika Panda's Research Ecosystem
- PyBullet (https://github.com/bulletphysics/bullet3)
- OpenAI Gym (https://github.com/openai/gym)
- DeepMind Control Suite (https://github.com/deepmind/dm_control)
- ROS 2 (Robot Operating System 2) (https://github.com/ros2)
- Gazebo (https://github.com/osrf/gazebo)
- Ignition Gazebo (https://github.com/gazebosim/gz-sim)
AI recommended 15 alternatives but never named PRIME-RL/SimpleVLA-RL. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of PRIME-RL/SimpleVLA-RL?passAI did not name PRIME-RL/SimpleVLA-RL — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts PRIME-RL/SimpleVLA-RL in production, what risks or prerequisites should they evaluate first?passAI named PRIME-RL/SimpleVLA-RL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo PRIME-RL/SimpleVLA-RL solve, and who is the primary audience?passAI named PRIME-RL/SimpleVLA-RL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
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PRIME-RL/SimpleVLA-RL — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite